Trial reportScientific reports2019
Cardiovascular risk algorithms in primary care: Results from the DETECT study.
Trial report in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 26 citations in OpenAlex.
- Statins for primary prevention of cardiovascular disease in Germany: benefits and costs.Clinical research in cardiology : official journal of the German Cardiac Society · 2026Article
- Risk of cardiovascular disease in Germany: results from GEDA 2022.Journal of health monitoring · 2025Article
- Resource Efficient Screening for Primary Prevention of Coronary Heart Disease: A Proof-of-Concept Test in the MESA Cohort.Journal of the American Heart Association · 2025Article
- Association of Metabolic Diseases and Moderate Fat Intake with Myocardial Infarction Risk.Nutrients · 2024Article
- Evidence supporting the choice of a new cardiovascular risk equation for Australia.The Medical journal of Australia · 2023Review
- Diagnostic Cardiac CT for the Improvement of Cardiovascular Event Prediction.Deutsches Arzteblatt international · 2023Article
- Integration of Risk Scores and Integration Capability in Electronic Patient Records.Applied clinical informatics · 2022Article
- Validation of Cardiovascular Risk Prediction by the Arriba Instrument.Deutsches Arzteblatt international · 2022Article
- Potentials of community-based early detection of cardiovascular disease risk during the COVID-19 pandemic.BMC public health · 2021Article
- Article
- Geographic and Sociodemographic Disparities in Cardiovascular Risk in Burkina Faso: Findings from a Nationwide Cross-Sectional Survey.Risk management and healthcare policy · 2021Article
- Outcomes in CME/CPD - Special Collection: How to make the "pyramid" a perpetuum mobile.Journal of European CME · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
13 authors at 10 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Guidelines for prevention of cardiovascular diseases use risk scores to guide the intensity of treatment. A comparison of these scores in a German population has not been performed. We have evaluated the correlation, discrimination and calibration of ten commonly used risk equations in primary care in 4044 participants of the DETECT (Diabetes and Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study. The risk equations correlate well with each other. All risk equations have a similar discriminatory power. Absolute risks differ widely, in part due to the components of clinical endpoints predicted: The risk equations produced median risks between 8.4% and 2.0%. With three out of 10 risk scores calculated and observed risks well coincided. At a risk threshold of 10 percent in 10 years, the ACC/AHA atherosclerotic cardiovascular disease (ASCVD) equation has a sensitivity to identify future CVD events of approximately 80%, with the highest specificity (69%) and positive predictive value (17%) among all the equations. Due to the most precise calibration over a wide range of risks, the large age range covered and the combined endpoint including non-fatal and fatal events, the ASCVD equation provides valid risk prediction for primary prevention in Germany.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.